Anelise P. Braga

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This paper aims at providing insights onto fundamental properties of two of the earlier models of matrix memories: non-linear, or Willshaw's matrix model, and the linear matrix memory. These are traditional models of Arti cial Neural Networks (ANNs) on which little has been done in recent years on themes such as retrieval and storage properties, which are(More)
A two-step optimization strategy for relational schemas that contains a class of inclusion dependencies is described. Both steps take into account additional information that indicates how to preserve each inclusion dependency in the presence of insertions an‘d deletioy. The first step eliminates inclusion dependencies which are redundant with respect to(More)
Arti cial Neural Networks are used to invert the potential energy function for diatomic molecules. The latter was based on radial basis function technique. Fifteen diatomic systems were used and leave-three-out for testing the learning procedure. The relative average error of the inverted potential compared against the exact one is about 5% which is(More)
Inversion of positron annihilation lifetime spectroscopy, based on a neural network Hopfield model, is presented in this paper. From a previous reported density function for lysozyme in water a simulated spectrum, without the superposition of statistical fluctuation and spectrometer resolution effects, was generated. These results were taken as the exact(More)
The aim of this work is to present a new training algorithm for SVMs based on the pattern selection strategy called Error Dependent Repetition (EDR). With EDR, the presentation frequency of a pattern depends on its error: patterns with larger errors are selected more frequently and patterns with smaller error (or learned) are presented with minor frequency.(More)
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